{"id":"W4392107087","doi":"10.1111/jbg.12859","title":"Characterization of runs of homozygosity islands in American mink using whole‐genome sequencing data","year":2024,"lang":"en","type":"article","venue":"Journal of Animal Breeding and Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Guelph; Dalhousie University","funders":"Nova Scotia Mink Breeders Association; Natural Sciences and Engineering Research Council of Canada; Alliance de recherche numérique du Canada; Mitacs; Department of Agriculture, Nova Scotia; Mink Veterinary Consulting and Research Service; Canada Mink Breeders Association","keywords":"Biology; Mink; Genetics; KEGG; Genome; Runs of Homozygosity; Gene; Whole genome sequencing; Population; Gene ontology; Single-nucleotide polymorphism; Gene expression","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002661489,0.00009347097,0.0002094673,0.0001024523,0.00002018869,0.00001726079,0.0001953253,0.00006270955,0.000002015224],"category_scores_gemma":[0.0000283163,0.00008640612,0.00004033888,0.0001364545,0.0001175921,0.000009195443,0.0001169228,0.0001026224,8.99476e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001178243,"about_ca_system_score_gemma":0.0001372594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001290349,"about_ca_topic_score_gemma":0.000006850178,"domain_scores_codex":[0.9991885,0.00002772602,0.0003918483,0.0001542823,0.0001234594,0.0001141579],"domain_scores_gemma":[0.9994685,0.00001427657,0.0002368043,0.0001454692,0.00008740766,0.00004756644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000695199,0.00002107067,0.008861354,0.00008534751,0.00004641603,0.000002310878,0.0003901872,0.0002177574,0.9883353,0.00002925131,0.000007483771,0.001934072],"study_design_scores_gemma":[0.0008970773,0.007010783,0.6587346,0.0006571687,0.0003021236,0.000505245,0.001299267,0.006211777,0.3214346,0.000256436,0.002272315,0.0004186822],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908332,0.001886942,0.006961078,0.00003587741,0.0001070723,0.00004015666,0.00009875741,0.000001365905,0.0000355811],"genre_scores_gemma":[0.9859462,0.0004146387,0.01331119,0.00001319885,0.0002620185,1.282852e-7,0.00002851533,0.00001166732,0.00001242561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6669006,"threshold_uncertainty_score":0.3523539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0388438302818606,"score_gpt":0.2840280034716182,"score_spread":0.2451841731897575,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}